SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Artículos que citan SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Título / Autor	Año
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille IEEE transactions on pattern analysis and machine intelligence 40 (4), 834-848	2017
The cityscapes dataset for semantic urban scene understanding M Cordts, M Omran, S Ramos, T Rehfeld, M Enzweiler, R Benenson, ... Proceedings of the IEEE conference on computer vision and pattern …	2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size FN Iandola, S Han, MW Moskewicz, K Ashraf, WJ Dally, K Keutzer arXiv preprint arXiv:1602.07360	2016
Pyramid scene parsing network H Zhao, J Shi, X Qi, X Wang, J Jia Proceedings of the IEEE conference on computer vision and pattern …	2017
Stacked hourglass networks for human pose estimation A Newell, K Yang, J Deng European conference on computer vision, 483-499	2016
Refinenet: Multi-path refinement networks for high-resolution semantic segmentation G Lin, A Milan, C Shen, I Reid Proceedings of the IEEE conference on computer vision and pattern …	2017
Encoder-decoder with atrous separable convolution for semantic image segmentation LC Chen, Y Zhu, G Papandreou, F Schroff, H Adam Proceedings of the European conference on computer vision (ECCV), 801-818	2018
What uncertainties do we need in bayesian deep learning for computer vision? A Kendall, Y Gal Advances in neural information processing systems, 5574-5584	2017
Enet: A deep neural network architecture for real-time semantic segmentation A Paszke, A Chaurasia, S Kim, E Culurciello arXiv preprint arXiv:1606.02147	2016
Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding A Kendall, V Badrinarayanan, R Cipolla arXiv preprint arXiv:1511.02680	2015
The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation S Jégou, M Drozdzal, D Vazquez, A Romero, Y Bengio Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
System, method, and computer program product for resolving addressing in a network including a network address translator TS Kennedy, JS Skelton, E Galinsky, A Staniforth, HJ Goldberg US Patent 7,797,433	2010
Scene parsing through ade20k dataset B Zhou, H Zhao, X Puig, S Fidler, A Barriuso, A Torralba Proceedings of the IEEE conference on computer vision and pattern …	2017
A review on deep learning techniques applied to semantic segmentation A Garcia-Garcia, S Orts-Escolano, S Oprea, V Villena-Martinez, ... arXiv preprint arXiv:1704.06857	2017
Monocular 3d object detection for autonomous driving X Chen, K Kundu, Z Zhang, H Ma, S Fidler, R Urtasun Proceedings of the IEEE Conference on Computer Vision and Pattern …	2016
Understanding convolution for semantic segmentation P Wang, P Chen, Y Yuan, D Liu, Z Huang, X Hou, G Cottrell 2018 IEEE winter conference on applications of computer vision (WACV), 1451-1460	2018
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics A Kendall, Y Gal, R Cipolla Proceedings of the IEEE Conference on Computer Vision and Pattern …	2018
Multinet: Real-time joint semantic reasoning for autonomous driving M Teichmann, M Weber, M Zoellner, R Cipolla, R Urtasun 2018 IEEE Intelligent Vehicles Symposium (IV), 1013-1020	2018
Salient Region Segmentation S He, N Pugeault arXiv preprint arXiv:1803.05759	2018
Semantic autoencoder for zero-shot learning E Kodirov, T Xiang, S Gong Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017

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